Technical Field
The present invention relates generally to information processing and, in particular, to scalable end-to-end Quality of Service (QoS) monitoring and diagnosis in Software Defined Networks (SDNs).
Description of the Related Art
While many network monitoring techniques/tools are available commercially and discussed in the literature, the monitoring of heterogeneous, large-scale network flows efficiently and accurately (i.e., without impacting the very network measured) suffers from significant limitations. Typically, existing monitoring techniques monitor the network infrastructure and the network devices and focus on service outages or black-outs. The monitoring of brown-outs, i.e., networks problems that degrade application performance without causing a complete failure are much harder to detect since they require large scale flow monitoring. Such flow monitoring (irrespective of whether active or passive) puts stress on the monitored network and there is a trade-off between overhead and accuracy. Furthermore, solutions that rely on instrumenting applications are not applicable to all network flows.
To improve cloud and network management, an application-agnostic, scalable monitoring solution that seamlessly applies to a diverse set of flows seamlessly is needed. The solution should provide visibility on the end-to-end performance accurately and with minimal overhead without impacting the underlying network.